https://wiki.cs.hse.ru/api.php?action=feedcontributions&feedformat=atom&user=Okhamisov 2026-09-21T13:28:17Z Вклад MediaWiki 1.43.9 https://wiki.cs.hse.ru/index.php?title=Optimisation_methods_2023/24&diff=81118 2023-10-24T14:59:28Z

<p>Okhamisov: корректировка опечаток</p> <hr /> <div><br /> <br /> == Main information about the course ==<br /> Course &quot;Optimization methods&quot; consists of several most important topics devoted to the theory of optimization and efficient optimization algorithms.<br /> During the course students will study <br /> <br /> - theoretical part: necessary and sufficient optimality conditions in unconstrained and constrained optimization;<br /> <br /> - practical part: zero, first and second order optimization algorithms, their implementation (for example, in Python) and testing.<br /> <br /> The leading objective of the course is the following: students must be able to classify a given optimization problem and select an efficient alforithm for finding solution.<br /> <br /> Teacher: Oleg Khamisov.<br /> <br /> Assistants: Andrey Ignatov, Marco Krsmanovich.<br /> <br /> == Grading ==<br /> <br /> Grade FG - Final grade, for the course is determined by the formula:<br /> <br /> FG=0.7*(CT1+CT2+CT3)+0.3*FT,<br /> <br /> where CT - Control Testing 1,2, and 3,<br /> <br /> FT - Final Testing.<br /> <br /> All testings consist of tasks, devoted to different topics of the course.<br /> <br /> Numbers CT1, CT2, CT3, and FT are such that in the case of successfull solution of all testings, final grading FG is equal to 10.<br /> <br /> == Retake rules ==<br /> The retake will consist of solving Additional Testing (AT) tasks. The maximal value of the AT is 5.</div>

Okhamisov https://wiki.cs.hse.ru/index.php?title=Optimisation_methods_2023/24&diff=80931 2023-10-16T05:04:06Z

<p>Okhamisov: Добавлено правило пересдачи э</p> <hr /> <div><br /> <br /> == Main information about the course ==<br /> Course &quot;Optimization methods&quot; consists of several most important topics devoted to the theory of optimization and efficient optimization algorithms.<br /> During the course students will study <br /> <br /> - theoretical part: necessary and sufficient optimality conditions in unconstrained and constrained optimization;<br /> <br /> - practical part: zero, first and second order optimization algorithms, their implementation (for example, in Python) and testing.<br /> <br /> The leading objective of the course is the following: students must be able to classify a given optimization problem and select an efficient alforithm for finding solution.<br /> <br /> Teacher: Oleg Khamisov.<br /> <br /> Assistants: Andrey Ignatov, Marco Krsmanovich.<br /> <br /> == Grading ==<br /> <br /> Grade FG - Final grade, for the course is determined by the formula:<br /> <br /> FG=0.7*(CT1+CT2+CT3)+0.3*FT,<br /> <br /> where CT - Control Testing 1,2, and 3,<br /> <br /> FT - Final Testing.<br /> <br /> All testings consist of tasks, devoted to different topics of the course.<br /> <br /> Numbers CT1, CT2, CT3, and FT are such that in the case of succesfull sulution of all testings, final grading FG is equal to 10.<br /> <br /> == Retake rules ==<br /> The retake will consist of solving Additional Testing (AT) tasks. The maximal value of the AT is 5.</div>

Okhamisov https://wiki.cs.hse.ru/index.php?title=Optimisation_methods_2023/24&diff=80930 2023-10-16T04:47:15Z

<p>Okhamisov: Внесено краткое описание курса и правило получения итоговой оценки</p> <hr /> <div><br /> <br /> == Main information about the course ==<br /> Course &quot;Optimization methods&quot; consists of several most important topics devoted to the theory of optimization and efficient optimization algorithms.<br /> During the course students will study <br /> <br /> - theoretical part: necessary and sufficient optimality conditions in unconstrained and constrained optimization;<br /> <br /> - practical part: zero, first and second order optimization algorithms, their implementation (for example, in Python) and testing.<br /> <br /> The leading objective of the course is the following: students must be able to classify a given optimization problem and select an efficient alforithm for finding solution.<br /> <br /> Teacher: Oleg Khamisov.<br /> <br /> Assistants: Andrey Ignatov, Marco Krsmanovich.<br /> <br /> == Grading ==<br /> <br /> Grade FG - Final grade, for the course is determined by the formula:<br /> <br /> FG=0.7*(CT1+CT2+CT3)+0.3*FT,<br /> <br /> where CT - Control Testing 1,2, and 3,<br /> <br /> FT - Final Testing.<br /> <br /> Numbers CT1, CT2, CT3, and FT are such that in the case of succesfull sulution of all testings final grading FT is equal to 10.</div>

Okhamisov